World J Mens Health.  2023 Jul;41(3):712-723. 10.5534/wjmh.220231.

OGT and FLAD1 Genes Had Significant Prognostic Roles in Progressive Pathogenesis in Prostate Cancer

Affiliations
  • 1Department of Urology, Center for Urological Cancer, National Cancer Center, Goyang, Korea
  • 2Department of Pathology, National Cancer Center, Goyang, Korea
  • 3Department of Medical Informatics, College of Medicine, The Catholic University, Seoul, Korea
  • 4Research Institute, National Cancer Center, Goyang, Korea
  • 5Department of Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
  • 6Biomedical Statistics Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea
  • 7Precision Medicine Research Center, College of Medicine, The Catholic University, Seoul, Korea
  • 8Cancer Evolution Research Center, College of Medicine, The Catholic University, Seoul, Korea

Abstract

Purpose
This study aimed to identify metabolic genes associated with non-metastatic prostate cancer progression using The Cancer Genome Atlas (TCGA) datasets and validate their prognostic role by assessing patients’ immunohistochemical prostatectomy specimens.
Materials and Methods
Several metabolic candidate genes analyzed were highly correlated with cancer progression to biochemical recurrence (BCR) and deaths in 335 patients’ genetic information from TCGA datasets. Those candidate genes and their expressions in tissue specimens were validated retrospectively by immunohistochemical analysis of radical prostatectomy specimens collected from 514 consecutive patients with non-metastatic prostate cancer between 2000 and 2015. The Cox proportional-hazards model was used to predict the prognostic role of each candidate gene expression in BCR and survival prognoses with a statistical significance of p-value <0.05. Twenty metabolic genes were identified by own developed software (Targa; https://github.com/cgab-ncc/TarGA), whose median expression levels consistently increased with cancer progression to the BCR and deaths.
Results
Five metabolic genes (MAT2A, FLAD1, UGDH, OGT, and RRM2) were found to be significantly involved in the overall survival in the TCGA dataset. The immunohistochemical validation and clinicopathological data showed that OGT (hazard ratio [HR], 1.002; 95% confidence interval [CI], 1.001–1.003) and FLAD1 (HR, 1.010; 95% CI, 1.003–1.017) remained significant factors for BCR and cancer-specific survival, respectively, in the multivariate analysis even after adjusting for confounding clinicopathological parameters (p<0.05).
Conclusions
OGT and FLAD1 showed significant prognostic factors of disease progression, even after adjustment for confounding clinicopathological parameters in non-metastatic prostate cancer.

Keyword

Big data; Metabolism; Prostate cancer; Tumor staging
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